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Article: Probing Lexical Ambiguity in Chinese Characters via Their Word Formations: Convergence of Perceived and Computed Metrics

TitleProbing Lexical Ambiguity in Chinese Characters via Their Word Formations: Convergence of Perceived and Computed Metrics
Authors
KeywordsChinese characters
Distributional semantics
Lexical ambiguity
Vector space models
Word formation
Issue Date21-Nov-2023
PublisherWiley
Citation
Cognitive Science: A Multidisciplinary Journal, 2023, v. 47, n. 11 How to Cite?
Abstract

Lexical ambiguity is pervasive in language, and the nature of the representations of an ambiguous word's multiple meanings is yet to be fully understood. With a special focus on Chinese characters, the present study first established that native speaker's perception about a character's number of meanings was heavily influenced by the availability of its distinct word formations, while whether these meanings would be perceived to be closely related was driven by further conceptual analysis. These notions were operationalized as two computed metrics, which assessed the degree of dispersion across individual word formations and the degree of propinquity across clusters of word formations, respectively, in a distributional semantic space. The observed correlations between the computed and the perceived metrics indicated that the utility of word formations to tap into meaning representations of Chinese characters was indeed cognitively plausible. The results have demonstrated the extent to which distributional semantics could inform about meaning representations of Chinese characters, which has theoretical implications for the representation of ambiguous words more generally.


Persistent Identifierhttp://hdl.handle.net/10722/345958
ISSN
2023 Impact Factor: 2.3
2023 SCImago Journal Rankings: 1.082

 

DC FieldValueLanguage
dc.contributor.authorWang, Tianqi-
dc.contributor.authorXu, Xu-
dc.contributor.authorXie, Xurong-
dc.contributor.authorNg, Manwa Lawrence-
dc.date.accessioned2024-09-04T07:06:46Z-
dc.date.available2024-09-04T07:06:46Z-
dc.date.issued2023-11-21-
dc.identifier.citationCognitive Science: A Multidisciplinary Journal, 2023, v. 47, n. 11-
dc.identifier.issn0364-0213-
dc.identifier.urihttp://hdl.handle.net/10722/345958-
dc.description.abstract<p>Lexical ambiguity is pervasive in language, and the nature of the representations of an ambiguous word's multiple meanings is yet to be fully understood. With a special focus on Chinese characters, the present study first established that native speaker's perception about a character's number of meanings was heavily influenced by the availability of its distinct word formations, while whether these meanings would be perceived to be closely related was driven by further conceptual analysis. These notions were operationalized as two computed metrics, which assessed the degree of dispersion across individual word formations and the degree of propinquity across clusters of word formations, respectively, in a distributional semantic space. The observed correlations between the computed and the perceived metrics indicated that the utility of word formations to tap into meaning representations of Chinese characters was indeed cognitively plausible. The results have demonstrated the extent to which distributional semantics could inform about meaning representations of Chinese characters, which has theoretical implications for the representation of ambiguous words more generally.<br></p>-
dc.languageeng-
dc.publisherWiley-
dc.relation.ispartofCognitive Science: A Multidisciplinary Journal-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectChinese characters-
dc.subjectDistributional semantics-
dc.subjectLexical ambiguity-
dc.subjectVector space models-
dc.subjectWord formation-
dc.titleProbing Lexical Ambiguity in Chinese Characters via Their Word Formations: Convergence of Perceived and Computed Metrics-
dc.typeArticle-
dc.identifier.doi10.1111/cogs.13379-
dc.identifier.scopuseid_2-s2.0-85177553755-
dc.identifier.volume47-
dc.identifier.issue11-
dc.identifier.eissn1551-6709-
dc.identifier.issnl0364-0213-

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